Haibin Lin
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- Advanced Neural Network Applications 7
- Advanced Vision and Imaging 2
- Multimodal Machine Learning Applications 2
- Artificial Intelligence top 5%
- Topic Modeling 3
- Stochastic Gradient Optimization Techniques 2
- Media Technology top 5%
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- Computer Graphics and Visualization Techniques 3
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- Parallel Computing and Optimization Techniques 3
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- Conducting polymers and applications 2
- Partner nations
- ChinaUnited StatesGermany
In The Last Decade
Haibin Lin
13 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 143
- Computer Vision and Pattern Recognition 502
- Artificial Intelligence 455
- Media Technology 103
- Computational Mathematics 5
- Computer Networks and Communications 179
Countries citing papers authored by Haibin Lin
This map shows the geographic impact of Haibin Lin's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Haibin Lin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Haibin Lin more than expected).
Fields of papers citing papers by Haibin Lin
This network shows the impact of papers produced by Haibin Lin. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Haibin Lin. The network helps show where Haibin Lin may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Haibin Lin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2025 | 1 | |
| 5 | 2024 | 8 | |
| 6 | 2024 | 45 | |
| 7 | 2024 | 0 | |
| 8 | 2024 | 1 | |
| 9 | 2023 | 14 | |
| 10 | ResNeSt: Split-Attention Networksbreakdown → | 2022 | 629 |
| 11 | GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing | 2020 | 109 |
| 12 | CSER: Communication-efficient SGD with Error Reset. | 2020 | 6 |
| 13 | 2020 | 36 | |
| 14 | Deep Graph Library: Towards Efficient and Scalable Deep Learning on Graphs | 2019 | 260 |
| 15 | Self-Driving Database Management Systems. | 2017 | 130 |
| 16 | 2013 | 1 | |
| 17 | 2013 | 0 | |
| 18 | 2013 | 3 |
About Haibin Lin
Haibin Lin is a scholar working on Computational Mathematics, Computer Graphics and Computer-Aided Design and Computer Vision and Pattern Recognition, having authored 18 papers that have together received 1.2k indexed citations. Recurring topics across this work include Advanced Neural Network Applications (7 papers), Topic Modeling (3 papers), Computer Graphics and Visualization Techniques (3 papers), Parallel Computing and Optimization Techniques (3 papers), Conducting polymers and applications (2 papers), Advanced Vision and Imaging (2 papers), Stochastic Gradient Optimization Techniques (2 papers) and Multimodal Machine Learning Applications (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (502 citations), Artificial Intelligence (455 citations) and Media Technology (103 citations). Haibin Lin has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Alexander J. Smola, Mu Li, Tong He, Yi Zhu, Zhongyue Zhang, Hang Zhang, Jonas Mueller, Yue Sun, Zhi Zhang and R. Manmatha. Their work appears in journals such as Scientific Reports, Chemical Engineering Journal and Talanta.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.